Computer vision is a very popular use-case of machine learning and AI. Neural networks are trained with lots of image data and are then asked to classify a random image based on its characteristics. Data scientists and Machine Learning developers strive to increase the accuracy of this prediction.

What is this machine learning course about?

Dubbed as Machine Learning Practica, this newly added interactive course will walk the students through the basics of machine learning and its application in image classification – one of the most important use-cases of Computer Vision. They will start with understanding the basics of image classification, and go on to learn about Convolutional Neural Networks, the neural network model that can be best used for image classification. This course will also teach the readers how to build a CNN from scratch, and demonstrate the best practices in training a highly effective and accurate model for classification. Topics such as preventing over-fitting, using pre-trained models and more, are also covered.

The course is primarily aimed at developers with a basic knowledge of machine learning. The examples and exercises included in this course are written in Keras – a highly popular Python library for training neural networks. While prior experience in Keras is not required, some exposure to Python programming will make it easier for you to get the best out of this course.

Google’s data scientists and researchers have collaborated with the image model experts to develop this course.It contains video, interactive programming exercises as well as relevant documentation for reference. The techniques highlighted in this course are already being used to power search in Google Photos.

Till date, more than 10,000 developers have benefited from this course. So, what are you waiting for? Get started with image classification in machine learning!